Lab 4 rmarkdown

Exercise 1: Add title and labels for the x and y axis to Lab3 ex1. Color the bars blue

library(ggplot2)
SNPs<- read.table("23andMe_complete.txt", header = TRUE, sep = "\t")
ggplot(data = SNPs) +
  geom_bar(mapping = aes(x=SNPs$chromosome), fill="blue") + 
  ggtitle("SNP Counts for Each Chromosome") + 
  scale_x_discrete(name="Chromosome Number") +
  scale_y_continuous(name="SNP Count")

Exercise 2: To Lab3 ex3 add more defined x and y axis labels, add a title, Change the colors of the genotypes, so that the dinucleotides (e.g. AA) are one color, the mononucleotides (A) are another and D’s and I’s a third color. One way to do this is to specify the color of each genotype.

SNPs$chromosome = ordered(SNPs$chromosome, levels=c(seq(1, 22), "X", "Y", "MT"))
genotypecolors <-c("AA"="blue", "AC"="blue", "AG"="blue", "AT"="blue", "CC"="blue", "CG"="blue", "CT"="blue", "GG"="blue", "GT"="blue", "TT"="blue", "A"="red", "C"="red", "G"="red", "T"="red", "D"="green", "DD"="green", "DI"="green", "DI"="green","I"="green", "II"="green")


ggplot(data = SNPs) +
  geom_bar(mapping = aes(x=SNPs$chromosome, fill=SNPs$genotype)) + 
  ggtitle("Contribution of each Genotype to Total SNP Count") +
  scale_x_discrete(name="Chromosome Number") +
  scale_y_continuous(name="SNP Count") +
  scale_fill_manual(values= genotypecolors)

Exercise 3: From Lab3 ex5, make an output png file, then load the file into report using the RMarkdown or html format.

Genotype counts per chromosome

Exercise 4: For Lab3 ex6 add more defined x and y axis labels, add a title, make the x-axis for each graph readable in your final report file.

SNPs$chromosome = ordered(SNPs$chromosome, levels=c(seq(1, 22), "X", "Y", "MT"))

ggplot(data = SNPs) +
  geom_bar(mapping = aes(x= chromosome, fill= genotype), position = "dodge") + 
  facet_wrap(~genotype, ncol= 2) +
  scale_x_discrete(name= "chromosome number") +
  scale_y_continuous(name= "Number of SNPs") +
  ggtitle("Genotype Levels in Each Chromosome")

Exercise 5: Turn Lab3 ex6 into an interactive graph using plotly

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

SNPs$chromosome = ordered(SNPs$chromosome, levels=c(seq(1,22), "X", "Y", "MT"))
ggplotly(
  ggplot(data = SNPs) + 
    geom_bar(mapping = aes(x = chromosome, fill = genotype), position = "dodge") + 
    facet_wrap(~genotype, nrow = 2)
)

Exercise 6: Make an interactive table of the SNPS found in on the Y chromosome from the 23andMe_complete data

YSNP <- subset(SNPs, chromosome=="Y")
library(DT)
datatable(YSNP)

## Warning in instance$preRenderHook(instance): It seems your data is too big
## for client-side DataTables. You may consider server-side processing: https://
## rstudio.github.io/DT/server.html